{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "import openslide\n",
    "import h5py\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import torch\n",
    "import json\n",
    "from modules.mhim import MHIM\n",
    "from modules.sam import sam_mil\n",
    "import cv2\n",
    "import random\n",
    "import seaborn as sns\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_area(pos_anchors,margin_percentage = 2,center_anchors=None,width_height=None):\n",
    "    if center_anchors is not None:\n",
    "        margin = 10 * 512 * margin_percentage / 2\n",
    "        center_anchor = (center_anchors[1],center_anchors[0])\n",
    "    else:\n",
    "        top, down, left, right = min(pos_anchors[:, 1]), max(pos_anchors[:, 1]), min(pos_anchors[:, 0]), max(pos_anchors[:, 0])\n",
    "        center_anchor = ((top + down) // 2, (left + right) // 2)\n",
    "        margin = max((down - top), (right - left)) * margin_percentage / 2\n",
    "\n",
    "    top, down, left, right = np.array(\n",
    "        [center_anchor[0]-margin, center_anchor[0]+margin, center_anchor[1]-margin, center_anchor[1]+margin],\n",
    "        dtype=int\n",
    "    )\n",
    "    ori_coord = np.array([down,top,right,left])\n",
    "    top,down,left,right = np.clip(top,0,width_height[1]),np.clip(down,0,width_height[1]),np.clip(left,0,width_height[0]),np.clip(right,0,width_height[0])\n",
    "    _gap = np.array([down,top,right,left]) \n",
    "    _coord = np.array([top,down,left,right]) \n",
    "    top,down,left,right = _coord + (_gap - ori_coord)\n",
    "\n",
    "    return top,down,left,right,(down-top) * (right-left)\n",
    "    \n",
    "def screen_coords(scores, coords, top_left, bot_right,cam=None):\n",
    "    bot_right = np.array(bot_right)\n",
    "    top_left = np.array(top_left)\n",
    "    mask = np.logical_and(np.all(coords >= top_left, axis=1), np.all(coords <= bot_right, axis=1))\n",
    "    if cam is not None:\n",
    "        return scores[mask], coords[mask], cam[mask]\n",
    "    else:\n",
    "        return scores[mask], coords[mask]\n",
    "\n",
    "def random_area(width,height,min_area,max_area):\n",
    "    while True:\n",
    "        left = random.randint(0, width - 1)\n",
    "        top = random.randint(0, height - 1)\n",
    "        right = random.randint(left + 1, width)\n",
    "        down = random.randint(top + 1, height)\n",
    "        area = (right - left) * (down - top)\n",
    "        if min_area <= area <= max_area:\n",
    "            return (top, left, down, right)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<All keys matched successfully>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# SAM-MIL\n",
    "mask = sam_mil(da_act='relu',baseline='attn').eval()\n",
    "mask.requires_grad_(False)\n",
    "\n",
    "mask_cpt = torch.load('/home/xxx/data/mil/vis/model/title/fold_1_model_best_auc.pt',map_location='cpu')\n",
    "\n",
    "mask.load_state_dict(mask_cpt['model'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<All keys matched successfully>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# AB-MIL\n",
    "pure = MHIM(da_act='relu',baseline='attn').eval()   # mhim's pure model of abmil\n",
    "pure.requires_grad_(False)\n",
    "\n",
    "pure_cpt = torch.load('/home/xxx/data/mil/vis/model/da_pure/fold_1_model_best_auc.pt',map_location='cpu')\n",
    "\n",
    "pure.load_state_dict(pure_cpt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "f_id = 'tumor_014'\n",
    "tif_path = \"/home/xxx/data/mil/c16/slide/\"+f_id+\".tif\"\n",
    "json_path = \"/home/xxx/data/mil/c16/json/\"+f_id+\".json\"\n",
    "h5_path = \"/home/xxx/data/mil/c16_clam_bio_seg/h5/\"+f_id+\".h5\"\n",
    "slide = openslide.OpenSlide(tif_path)\n",
    "width, height = slide.dimensions\n",
    "# load anno\n",
    "try:\n",
    "    with open(json_path, 'r') as f:\n",
    "        json_data = json.load(f)\n",
    "except:\n",
    "    json_data = None\n",
    "    print('Normal slide')\n",
    "patch = h5py.File(h5_path,\"r\")\n",
    "features = torch.Tensor(patch['features'])\n",
    "coords = np.array(patch['coords'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_8433/2625244135.py:8: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  pred = torch.nn.functional.softmax(pred)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor(0.6070)"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def predict(f_id):\n",
    "    # h5_path = \"/home/xxx/data/mil/c16_clam_bio_seg/h5/\"+f_id+\".h5\"\n",
    "    h5_path = \"/nas/xxx/c16_bio_seg/data/feats/h5_files/\"+f_id+\".h5\"\n",
    "    patch = h5py.File(h5_path,\"r\")\n",
    "    features = torch.Tensor(patch['features'])\n",
    "    coords = np.array(patch['coords'])\n",
    "    pred,A = mask.forward_test(features, True,True)\n",
    "    A = A.squeeze()\n",
    "    pred = torch.nn.functional.softmax(pred)\n",
    "    return pred[0][0]\n",
    "predict('test_081')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_cam_1d(classifier, feat,attention):\n",
    "    attention = torch.nn.functional.softmax(attention)\n",
    "    features = torch.einsum('ns,n->ns', feat, attention)  ### n x fs\n",
    "    tweight = list(classifier.parameters())[-2]\n",
    "    cam_maps = torch.einsum('gf,cf->cg', features, tweight)\n",
    "    return cam_maps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[0.0012, 0.9988]])\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_26934/501866292.py:3: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  print(torch.nn.functional.softmax(pred_tea))\n",
      "/tmp/ipykernel_26934/501866292.py:4: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  len_keep,mask_ = tea.get_mask(features.size(0),0,torch.nn.functional.softmax(A_tea))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# tea\n",
    "pred_tea,A_tea = tea.forward_test(features, True, True)\n",
    "print(torch.nn.functional.softmax(pred_tea))\n",
    "len_keep,mask_ = tea.get_mask(features.size(0),0,torch.nn.functional.softmax(A_tea))\n",
    "A_mask = A_tea.clone()\n",
    "A_tea = A_tea.squeeze()\n",
    "A_mask[:] = 0\n",
    "_m = A_mask.clone()\n",
    "_m = _m.scatter_(1,mask_[:,:len_keep],1) == 1\n",
    "A_mask[_m] = 1\n",
    "A_mask = A_mask.squeeze()\n",
    "\n",
    "_a,_ = torch.sort(A_tea,descending=True)\n",
    "_a_vis = (_a - _a.min()) / (_a.max() - _a.min())\n",
    "sns.scatterplot(x=np.array(list(range(_a.size(0)))),y=_a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[0.0012, 0.9988]])\n",
      "tensor(0.6364)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_26934/920204557.py:4: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  print(torch.nn.functional.softmax(pred_m))\n",
      "/tmp/ipykernel_26934/3736863783.py:2: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  attention = torch.nn.functional.softmax(attention)\n",
      "/tmp/ipykernel_26934/920204557.py:12: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  A_m = torch.nn.functional.softmax(A_m)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# mask predition\n",
    "pred_m,A_m = mask.forward_test(features, True,True)\n",
    "A_m = A_m.squeeze()\n",
    "print(torch.nn.functional.softmax(pred_m))\n",
    "# cam\n",
    "cam_m = get_cam_1d(mask.predictor,mask.dp(mask.patch_to_emb(features.squeeze(0))),A_m)\n",
    "cam_m = torch.nn.functional.softmax(cam_m,dim=0)\n",
    "cam_m = cam_m[1]\n",
    "cam_thr = cam_m.max()\n",
    "print(cam_thr)\n",
    "# softmax\n",
    "A_m = torch.nn.functional.softmax(A_m)\n",
    "_a,_ = torch.sort(A_m,descending=True)\n",
    "_a_vis = (_a - _a.min()) / (_a.max() - _a.min())\n",
    "sns.scatterplot(x=np.array(list(range(_a.size(0)))),y=_a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[9.7710e-06, 9.9999e-01]])\n",
      "tensor(0.6364)\n",
      "tensor([0.9950, 0.8059, 0.7382])\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_26934/1617909186.py:4: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  print(torch.nn.functional.softmax(pred_b))\n",
      "/tmp/ipykernel_26934/3736863783.py:2: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  attention = torch.nn.functional.softmax(attention)\n",
      "/tmp/ipykernel_26934/1617909186.py:12: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  A_b = torch.nn.functional.softmax(A_b)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ab-mil\n",
    "pred_b,A_b = pure.forward_test(features, True,True)\n",
    "A_b = A_b.squeeze()\n",
    "print(torch.nn.functional.softmax(pred_b))\n",
    "# cam \n",
    "cam_b = get_cam_1d(pure.predictor,pure.dp(pure.patch_to_emb(features.squeeze(0))),A_b)\n",
    "cam_b = torch.nn.functional.softmax(cam_b,dim=0)\n",
    "cam_b = cam_b[1]\n",
    "print(cam_m.max())\n",
    "\n",
    "# softmax\n",
    "A_b = torch.nn.functional.softmax(A_b)\n",
    "#A_norm = (A - A.min()) / (A.max() - A.min())\n",
    "_a,_a_idx = torch.sort(A_b,descending=True)\n",
    "_cam,_cam_idx = torch.sort(cam_b,descending=True)\n",
    "print(_cam[:3])\n",
    "sns.scatterplot(x=np.array(list(range(_a.size(0)))),y=_a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'attn' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_6123/3658202826.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# compute A\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mpred\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mA\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mattn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0mA\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mA\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqueeze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfunctional\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msoftmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpred\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;31m# cam\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'attn' is not defined"
     ]
    }
   ],
   "source": [
    "# compute A\n",
    "pred,A = attn(features, True,True)\n",
    "A = A.squeeze()\n",
    "print(torch.nn.functional.softmax(pred))\n",
    "# cam\n",
    "# cam = get_cam_1d(attn.classifier[0],attn.feature(features.squeeze(0)),A)\n",
    "# # A = torch.nn.functional.softmax(cam[0])\n",
    "# A = cam[1]\n",
    "\n",
    "# softmax\n",
    "A = torch.nn.functional.softmax(A)\n",
    "A_norm = (A - A.min()) / (A.max() - A.min())\n",
    "_a,_ = torch.sort(A_norm,descending=True)\n",
    "sns.scatterplot(x=np.array(list(range(_a.size(0)))),y=_a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'swin' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_2478/1982631344.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# compute A\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mpred\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mA\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mswin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0mA\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mA\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqueeze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfunctional\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msoftmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpred\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;31m# softmax\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'swin' is not defined"
     ]
    }
   ],
   "source": [
    "# compute A\n",
    "pred,A = swin(features, True,True)\n",
    "A = A.squeeze()\n",
    "print(torch.nn.functional.softmax(pred))\n",
    "# softmax\n",
    "#A = torch.nn.functional.softmax(A)\n",
    "# cam\n",
    "cam = get_cam_1d(swin.predictor,swin.online_encoder(swin.dp(swin.patch_to_emb(features.squeeze(0))),no_pool=True),A)\n",
    "cam = torch.nn.functional.softmax(cam,dim=0)\n",
    "cam = cam[1]\n",
    "_a,_ = torch.sort(A,descending=True)\n",
    "_cam,_cam_idx = torch.sort(cam,descending=True)\n",
    "\n",
    "#sns.scatterplot(x=np.array(list(range(_a.size(0)))),y=_a)\n",
    "sns.scatterplot(x=np.array(list(range(_cam.size(0)))),y=_cam)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## find the roi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 21.75\n",
      "1 1.02734375\n",
      "2 9.1484375\n",
      "3 41.94140625\n",
      "6 2.40234375\n"
     ]
    }
   ],
   "source": [
    "patch_num = 1\n",
    "patch_size = 512\n",
    "if json_data is not None:\n",
    "    for _pos in range(len(json_data['positive'])):\n",
    "        _,_,_,_,area = get_area(np.array(json_data['positive'][_pos]['vertices']),width_height=[width,height])\n",
    "        if area >= (patch_size*patch_num)**2:\n",
    "            print(_pos,area**0.5 / patch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "crop_size = 512  \n",
    "stride = 512  \n",
    "vis_level = 3           \n",
    "vis_size = None # 448   \n",
    "roi = 3 # -1->global, i->roi_index, roi_index 对应上一个代码块的输出，对tumor slide有用\n",
    "alpha = .3  # 0-no_img,1-all_img\n",
    "margin_percentage = 1.5\n",
    "roi_coord = None  \n",
    "rel_norm = False  \n",
    "filter_thr = 0.4   \n",
    "filter_thr_cam = 0.5001 \n",
    "is_norm = True    \n",
    "save_figure = False\n",
    "vis_model = 'mask'  \n",
    "_c_cam = np.array([0,255,255])  \n",
    "_c_attn = np.array([255,255,255]) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Attention + CAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>>>>>>>>>>> region coord gotten >>>>>>>>>>>\n",
      ">>>>>>>>>>>> slide region gotten >>>>>>>>>>>\n",
      ">>>>>>>>>>cam_roi>>>>>>>>>>>>\n",
      "tensor([0.5680, 0.5953, 0.6033, 0.6075, 0.6350])\n",
      ">>>>>>>>>>>> relative coords computed >>>>>>>>>>>\n",
      ">>>>>>>>>>>> heatmap computed >>>>>>>>>>>\n",
      ">>>>>>>>>>>> heatmap draw done>>>>>>>>>>>\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plt.figure(figsize=(6,6),dpi=300)\n",
    "\n",
    "if vis_model == 'attn':\n",
    "    _A = A_b\n",
    "    __cam = cam_b\n",
    "    f_name = 'ABMIL_'\n",
    "elif vis_model == 'mask':\n",
    "    _A = A_m\n",
    "    __cam = cam_m\n",
    "    f_name = 'MASK_'\n",
    "\n",
    "if roi_coord is None:\n",
    "    if roi >= 0:\n",
    "        if json_data is not None:\n",
    "            pos_anchors = np.array(json_data['positive'][roi]['vertices'])\n",
    "            top,down,left,right,_ = get_area(pos_anchors,margin_percentage,width_height=[width,height])\n",
    "        else:\n",
    "            top,down,left,right,_ = get_area(None,margin_percentage,coords[_a_idx[0]],width_height=[width,height])\n",
    "    else:\n",
    "        top,down,left,right = 0,height,0,width\n",
    "    crop_coords = []\n",
    "    for i in range(top, down, stride):\n",
    "        for j in range(left, right, stride):\n",
    "            if j + crop_size > width or i + crop_size > height:\n",
    "                continue\n",
    "            crop_coords.append((j, i))\n",
    "    right, down = np.max(crop_coords, 0) + crop_size\n",
    "else:\n",
    "    top,down,left,right = roi_coord\n",
    "print(\">>>>>>>>>>>> region coord gotten >>>>>>>>>>>\")\n",
    "\n",
    "scale_level_ratio = np.array(slide.level_dimensions[vis_level]) / np.array(slide.level_dimensions[0])\n",
    "_w,_h = np.array((right-left, down-top))*scale_level_ratio\n",
    "# _w,_h = (right-left, down-top)\n",
    "region = slide.read_region((left, top), list(range(slide.level_count))[vis_level], (int(_w),int(_h))).convert('RGB')\n",
    "print(\">>>>>>>>>>>> slide region gotten >>>>>>>>>>>\")\n",
    "#\n",
    "A_roi,coords_roi,cam_roi = screen_coords(_A,coords,(left,top),(right,down),cam=__cam)\n",
    "print(\">>>>>>>>>>cam_roi>>>>>>>>>>>>\")\n",
    "sorted_indices = np.argsort(cam_roi)\n",
    "print(cam_roi[sorted_indices[-5:]])\n",
    "#\n",
    "img = np.array(region)\n",
    "# \n",
    "coords_roi_rel = []\n",
    "for i in range(len(coords_roi)):\n",
    "    rel_x = coords_roi[i][0]-left\n",
    "    rel_y = coords_roi[i][1] - top\n",
    "    rel_x,rel_y = np.clip(rel_x,0,right-left),np.clip(rel_y,0,down-top)\n",
    "    coords_roi_rel.append([rel_x,rel_y])\n",
    "print(\">>>>>>>>>>>> relative coords computed >>>>>>>>>>>\")\n",
    "# \n",
    "if is_norm:\n",
    "    if rel_norm:\n",
    "        A_roi = (A_roi - A_roi.min()) / (A_roi.max() - A_roi.min())\n",
    "    else:\n",
    "        A_roi = (A_roi - _A.min()) / (_A.max() - _A.min())\n",
    "A_roi[A_roi<filter_thr] = 0\n",
    "cam_roi[cam_roi <= filter_thr_cam] = 0\n",
    "\n",
    "heatmap_attn = np.zeros(img.shape)\n",
    "heatmap_cam = np.zeros(img.shape)\n",
    "alpha_mat_attn = np.ones(img.shape) * 0.5 * alpha\n",
    "alpha_mat_cam = np.ones(img.shape) * 0.5 * alpha\n",
    "\n",
    "for _idx,_coord in enumerate(coords_roi_rel):\n",
    "    A_flag = False\n",
    "    cam_flag = False\n",
    "\n",
    "    if A_roi[_idx] != 0:\n",
    "        heatmap_attn[int(_coord[1]*scale_level_ratio[1]):int((_coord[1]+patch_size)*scale_level_ratio[1]),int(_coord[0]*scale_level_ratio[0]):int((_coord[0]+patch_size)*scale_level_ratio[0]),:] = A_roi[_idx] * _c_attn\n",
    "        A_flag = True\n",
    "    if cam_roi[_idx] != 0:\n",
    "        alpha_mat_attn[int(_coord[1]*scale_level_ratio[1]):int((_coord[1]+patch_size)*scale_level_ratio[1]),int(_coord[0]*scale_level_ratio[0]):int((_coord[0]+patch_size)*scale_level_ratio[0]),:] = 0\n",
    "        heatmap_attn[int(_coord[1]*scale_level_ratio[1]):int((_coord[1]+patch_size)*scale_level_ratio[1]),int(_coord[0]*scale_level_ratio[0]):int((_coord[0]+patch_size)*scale_level_ratio[0]),:] = 0\n",
    "        alpha_mat_cam[int(_coord[1]*scale_level_ratio[1]):int((_coord[1]+patch_size)*scale_level_ratio[1]),int(_coord[0]*scale_level_ratio[0]):int((_coord[0]+patch_size)*scale_level_ratio[0]),:] = 1-cam_roi[_idx]\n",
    "\n",
    "        heatmap_cam[int(_coord[1]*scale_level_ratio[1]):int((_coord[1]+patch_size)*scale_level_ratio[1]),int(_coord[0]*scale_level_ratio[0]):int((_coord[0]+patch_size)*scale_level_ratio[0]),:] = _c_cam\n",
    "\n",
    "        cam_flag = True\n",
    "    else:\n",
    "        alpha_mat_cam[int(_coord[1]*scale_level_ratio[1]):int((_coord[1]+patch_size)*scale_level_ratio[1]),int(_coord[0]*scale_level_ratio[0]):int((_coord[0]+patch_size)*scale_level_ratio[0]),:] = 0\n",
    "\n",
    "    if not A_flag and not cam_flag:\n",
    "\n",
    "        alpha_mat_attn[int(_coord[1]*scale_level_ratio[1]):int((_coord[1]+patch_size)*scale_level_ratio[1]),int(_coord[0]*scale_level_ratio[0]):int((_coord[0]+patch_size)*scale_level_ratio[0]),:] = alpha\n",
    "print(\">>>>>>>>>>>> heatmap computed >>>>>>>>>>>\")\n",
    "#\n",
    "\n",
    "blended_image = (alpha_mat_attn * img + alpha_mat_cam*img + (1-alpha_mat_attn) * heatmap_attn + (1-alpha_mat_cam) * heatmap_cam)\n",
    "blended_image = blended_image.astype(np.uint8)\n",
    "\n",
    "if vis_size is not None:\n",
    "    plt.imshow(cv2.resize(blended_image,dsize=(vis_size,vis_size)))\n",
    "    scale_ratio = (vis_size / img.shape[0])*scale_level_ratio\n",
    "else:\n",
    "    plt.imshow(blended_image)\n",
    "    scale_ratio = scale_level_ratio\n",
    "print(\">>>>>>>>>>>> heatmap draw done>>>>>>>>>>>\")\n",
    "plt.xlim(0,(right-left)*scale_ratio[0])\n",
    "plt.ylim((down-top)*scale_ratio[1],0)\n",
    "plt.axis(\"off\")\n",
    "\n",
    "if json_data is not None:\n",
    "    for anchors in (json_data['positive']):\n",
    "        _pos_anchors = np.array(anchors['vertices'])\n",
    "        plt.plot((_pos_anchors[:, 0]-left) * scale_ratio[0] , (_pos_anchors[:,1]-top)* scale_ratio[1], color=(0,128/255,1),linewidth=3.0)\n",
    "\n",
    "# if save_figure:\n",
    "path = os.path.join(\"./vis_figure/sup/tumor/\",f_id+f_name+str(roi)+'.png')\n",
    "plt.savefig(path,dpi=450,bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Attention"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "vis_model = 'mask'  # attn or mask \n",
    "is_norm = True\n",
    "alpha=0.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>>>>>>>>>>> region coord gotten >>>>>>>>>>>\n",
      ">>>>>>>>>>>> slide region gotten >>>>>>>>>>>\n",
      ">>>>>>>>>>>> relative coords computed >>>>>>>>>>>\n",
      ">>>>>>>>>>>> heatmap computed >>>>>>>>>>>\n",
      ">>>>>>>>>>>> heatmap draw done>>>>>>>>>>>\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "if vis_model == 'attn':\n",
    "    _A = A_b\n",
    "    __cam = cam_b\n",
    "    f_name = 'ABMIL_'\n",
    "elif vis_model == 'mask':\n",
    "    _A = A_m\n",
    "    __cam = cam_m\n",
    "    f_name = 'MASK_'\n",
    "elif vis_model == 'tea':\n",
    "    _A = A_tea\n",
    "    f_name = 'TEA_'\n",
    "elif vis_model == 'sam':\n",
    "    _A = A_mask\n",
    "    f_name = 'TEA_'\n",
    "if roi_coord is None:\n",
    "    if roi >= 0:\n",
    "        if json_data is not None:\n",
    "            pos_anchors = np.array(json_data['positive'][roi]['vertices'])\n",
    "            top,down,left,right,_ = get_area(pos_anchors,margin_percentage,width_height=[width,height])\n",
    "        else:\n",
    "            top,down,left,right,_ = get_area(None,margin_percentage,coords[_a_idx[1]],width_height=[width,height])\n",
    "    else:\n",
    "        top,down,left,right = 0,height,0,width\n",
    "    crop_coords = []\n",
    "    # print(top,down,left,right)\n",
    "    for i in range(top, down, stride):\n",
    "        for j in range(left, right, stride):\n",
    "            if j + crop_size > width or i + crop_size > height:\n",
    "                continue\n",
    "            crop_coords.append((j, i))\n",
    "    right, down = np.max(crop_coords, 0) + crop_size\n",
    "else:\n",
    "    top,down,left,right = roi_coord\n",
    "print(\">>>>>>>>>>>> region coord gotten >>>>>>>>>>>\")\n",
    "\n",
    "scale_level_ratio = np.array(slide.level_dimensions[vis_level]) / np.array(slide.level_dimensions[0])\n",
    "_w,_h = np.array((right-left, down-top))*scale_level_ratio\n",
    "# _w,_h = (right-left, down-top)\n",
    "region = slide.read_region((left, top), list(range(slide.level_count))[vis_level], (int(_w),int(_h))).convert('RGB')\n",
    "print(\">>>>>>>>>>>> slide region gotten >>>>>>>>>>>\")\n",
    "#\n",
    "A_roi,coords_roi = screen_coords(_A,coords,(left,top),(right,down))\n",
    "#\n",
    "img = np.array(region)\n",
    "# \n",
    "coords_roi_rel = []\n",
    "for i in range(len(coords_roi)):\n",
    "    rel_x = coords_roi[i][0]-left\n",
    "    rel_y = coords_roi[i][1] - top\n",
    "    rel_x,rel_y = np.clip(rel_x,0,right-left),np.clip(rel_y,0,down-top)\n",
    "    coords_roi_rel.append([rel_x,rel_y])\n",
    "print(\">>>>>>>>>>>> relative coords computed >>>>>>>>>>>\")\n",
    "# \n",
    "if is_norm:\n",
    "    if rel_norm:\n",
    "        A_roi = (A_roi - A_roi.min()) / (A_roi.max() - A_roi.min())\n",
    "    else:\n",
    "        A_roi = (A_roi - _A.min()) / (_A.max() - _A.min())\n",
    "A_roi[A_roi<filter_thr] = 0\n",
    "\n",
    "heatmap = np.zeros(img.shape)\n",
    "alpha_mat = np.ones(img.shape) *  alpha\n",
    "for _idx,_coord in enumerate(coords_roi_rel):\n",
    "    heatmap[int(_coord[1]*scale_level_ratio[1]):int((_coord[1]+patch_size)*scale_level_ratio[1]),int(_coord[0]*scale_level_ratio[0]):int((_coord[0]+patch_size)*scale_level_ratio[0]),:] = A_roi[_idx] * 255\n",
    "\n",
    "print(\">>>>>>>>>>>> heatmap computed >>>>>>>>>>>\")\n",
    "#\n",
    "blended_image = (alpha * img + (1-alpha) * heatmap[:, :, :3])\n",
    "blended_image = blended_image.astype(np.uint8)\n",
    "\n",
    "if vis_size is not None:\n",
    "    plt.imshow(cv2.resize(blended_image,dsize=(vis_size,vis_size)))\n",
    "    scale_ratio = (vis_size / img.shape[0])*scale_level_ratio\n",
    "else:\n",
    "    plt.imshow(blended_image)\n",
    "    scale_ratio = scale_level_ratio\n",
    "print(\">>>>>>>>>>>> heatmap draw done>>>>>>>>>>>\")\n",
    "plt.xlim(0,(right-left)*scale_ratio[0])\n",
    "plt.ylim((down-top)*scale_ratio[1],0)\n",
    "plt.axis(\"off\")\n",
    "\n",
    "if json_data is not None:\n",
    "    for anchors in (json_data['positive']):\n",
    "        _pos_anchors = np.array(anchors['vertices'])\n",
    "        plt.plot((_pos_anchors[:, 0]-left) * scale_ratio[0] , (_pos_anchors[:,1]-top)* scale_ratio[1], color='deepskyblue')\n",
    "\n",
    "path = os.path.join(\"./vis_figure/sup/tumor/\",f_id+f_name+str(roi)+'_attn.png')\n",
    "plt.savefig(path,dpi=450,bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Original Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>>>>>>>>>>> region coord gotten >>>>>>>>>>>\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "if roi_coord is None:\n",
    "    if roi >= 0:\n",
    "        if json_data is not None:\n",
    "            pos_anchors = np.array(json_data['positive'][roi]['vertices'])\n",
    "            top,down,left,right,_ = get_area(pos_anchors,margin_percentage,width_height=[width,height])\n",
    "        else:\n",
    "            top,down,left,right,_ = get_area(None,margin_percentage,coords[_a_idx[1]],width_height=[width,height])\n",
    "    else:\n",
    "        top,down,left,right = 0,height,0,width\n",
    "    crop_coords = []\n",
    "    # print(top,down,left,right)\n",
    "    for i in range(top, down, stride):\n",
    "        for j in range(left, right, stride):\n",
    "            if j + crop_size > width or i + crop_size > height:\n",
    "                continue\n",
    "            crop_coords.append((j, i))\n",
    "    right, down = np.max(crop_coords, 0) + crop_size\n",
    "else:\n",
    "    top,down,left,right = roi_coord\n",
    "print(\">>>>>>>>>>>> region coord gotten >>>>>>>>>>>\")\n",
    "\n",
    "scale_level_ratio = np.array(slide.level_dimensions[vis_level]) / np.array(slide.level_dimensions[0])\n",
    "_w,_h = np.array((right-left, down-top))*scale_level_ratio\n",
    "# _w,_h = (right-left, down-top)\n",
    "region = slide.read_region((left, top), list(range(slide.level_count))[vis_level], (int(_w),int(_h))).convert('RGB')\n",
    "\n",
    "\n",
    "plt.imshow(np.array(region))\n",
    "plt.axis(\"off\")\n",
    "plt.xlim(0,(right-left)*scale_ratio[0])\n",
    "plt.ylim((down-top)*scale_ratio[1],0)\n",
    "if json_data is not None:\n",
    "    for anchors in (json_data['positive']):\n",
    "        _pos_anchors = np.array(anchors['vertices'])\n",
    "        plt.plot((_pos_anchors[:, 0]-left) * scale_ratio[0] , (_pos_anchors[:,1]-top)* scale_ratio[1], color='deepskyblue')\n",
    "path = os.path.join(\"./vis_figure/sup/\",f_id+f_name+'_'+str(roi)+'_ori'+'.png')\n",
    "plt.savefig(path,dpi=450,bbox_inches='tight')"
   ]
  }
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